METHOD AND APPARATUS FOR EXTRACTING FEATURE POINTS FROM DIGITAL IMAGE
First Claim
1. A method of extracting feature points from a digital image in a multiprocessor system using a scale invariant feature transform (SIFT) technique, the method comprising:
- dividing an original image into a plurality of regions so as to be allocated to a plurality of processors of the multiprocessor system;
performing, by the plurality of processors, blurring operations by levels;
dividing the images blurred by levels into a plurality of regions to be allocated to the processors and calculating, by the plurality of processors, differences of Gaussian (DoGs); and
generating feature point data according to the calculated DoGs.
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Abstract
An apparatus and method for extracting feature points from an image in a multiprocessor system having a plurality of processors, the method including: dividing an original image into a plurality of regions so as to be allocated to a plurality of processors of the multiprocessor system; performing, by the plurality of processors, blurring operations by levels; dividing the images blurred by levels into a plurality of regions to be allocated to the processors and calculating, by the plurality of processors, differences of Gaussian (DoGs); and generating feature point data according to the calculated DoGs. Because a plurality of processors performs the operations of the method, the total time to extract the feature points from the image is significantly reduced.
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Citations
25 Claims
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1. A method of extracting feature points from a digital image in a multiprocessor system using a scale invariant feature transform (SIFT) technique, the method comprising:
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dividing an original image into a plurality of regions so as to be allocated to a plurality of processors of the multiprocessor system; performing, by the plurality of processors, blurring operations by levels; dividing the images blurred by levels into a plurality of regions to be allocated to the processors and calculating, by the plurality of processors, differences of Gaussian (DoGs); and generating feature point data according to the calculated DoGs. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A multiprocessor apparatus to extract feature points from a digital image according to a scale invariant feature transform (SIFT) technique, the apparatus comprising:
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a plurality of processors to perform blurring operations by levels on corresponding regions of the digital image and to calculate differences of Gaussian (DoGs) on corresponding regions of the images blurred by levels; and at least one processor to generate feature point data according to the calculated DoGs. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21)
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22. A method of extracting feature points from a digital image in a multiprocessor system using a scale invariant feature transform (SIFT) technique, the method comprising:
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dividing one or more image regions of the digital image blurred by levels into a plurality of regions to be allocated to a plurality of processors of the multiprocessor system; calculating, by the plurality of processors, differences of Gaussian (DoGs); and generating feature point data according to the calculated DoGs. - View Dependent Claims (23, 24, 25)
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Specification